Assessment of SAR Image Filtering using Adaptive Stack Filters

TL;DR

This paper evaluates the effectiveness of adaptive stack filters in enhancing SAR images by reducing noise while preserving details, using image quality metrics and classification accuracy as evaluation criteria.

Contribution

It provides an assessment of adaptive stack filters specifically applied to SAR images, highlighting their performance in noise reduction and detail preservation.

Findings

Adaptive stack filters improve SAR image quality.

Filtered images show better classification accuracy.

The study validates the effectiveness of stack filters for SAR noise reduction.

Abstract

Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is then filtered by a Boolean function, which characterizes the filter. Adaptive stack filters can be designed to be optimal; they are computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work we study the performance of adaptive stack filters when they are applied to Synthetic Aperture Radar (SAR) images. This is done by evaluating the quality of the filtered images through the use of suitable image quality indexes and by measuring the classification accuracy of the resulting images.